Article: More Barrels Per Data


People, Ideas, Innovation, Assets, Statistics and Exploration are some of the numerous areas that we deal with while thriving in a society abound in skill. The Petroleum Industry comprises of many parts. All these various areas generate a lot of information – from downstream, midstream, drilling, production, reservoir, geology and finance etc. The oil and gas industry has been a forefront when it comes to collecting information and utilizing it. The advent of computers, sensors and tools has allowed us to generate more data. Eventually, to make this vast load of data to talk, we analyze it. Big Data Analysis is a method to correlate, organize and arrange large sets of data in order to extract patterns and make wiser and practical decisions from observations.

Big Data Analysis has major implications in the oil and gas industry. Just consider a situation where one has predicted everything about a well before drilling, due to all the statistical operations that were performed on the geological readings taken from the region. It not only saves a lot of time and money, but also it maximizes yield and reduces risk at a higher reward. Given the right data, the right models and the right expertise, we can truly optimize and improve on the performance of the enterprise.

The future of Big Data:

As connected systems for oil and gas expand through the cloud, with the data flowing seamlessly from drill bit to burner tip, upstream production activity can account for changes in market conditions and energy demand without any human intervention. Consider for a moment, the global stock markets that are powered by sophisticated computing systems. Stock market computing systems make thousands of transactions per second, and the gain of fractions of a second is a competitive advantage over other trading systems.

Cloud computing encourages the efficient use of capital while expanding computing and storage capacity. And with today’s capabilities in machine learning, companies can expand beyond one scenario that engineers and management conceptualize, and instead run through many potential scenarios to produce the best path forward. Companies will continue to have better access to data from their trading partners and services providers including: devices in the field that stream real-time production data, real-time market and commodity pricing, and risks and the predictive models. Results from each of these business areas all play an important role in the recommendations that executives will use to direct their organizations through the ups and downs.

  • Land Management

Once we have acquired an asset, we can use a developmental engine to continuously revaluate asset and alter development plans according to the situations. In the world of IoT, a lot of data stream provide real time data about a location. The use of artificial intelligence technologies such as cognitive and natural language interpretation, any uncertainty in the data can be removed by applying an objective score. The application of a mobile device for scanning the lease and processing the context is essential to score the gathered inputs.

  • Drilling and Completion:

Data streaming is the new normal when it comes to drilling. Here, fiber optics are used to sample hundreds of sensors every few seconds and gather rates, pressures etc. Data models use hundreds of inputs that can be controlled like drill location, frac length, depth etc. Analytics find that 3D seismic data integration with their completion design improves the long term economics of every well drilled by increasing the oil/gas production and reducing the risk associated with well design.

  • Production Operations:

Production optimization is not solely dependent on producing more oil and gas all the time; to truly optimize production, companies must produce smarter with less overhead. Utilizing sensors and devices to capture downhole pressures and flow rates periodically. The equipment controlled data on high frequencies yields more accurate data sets, and improves an engineer’s ability to make production decisions. Intelligent systems must also deliver information back to the field technician in real time, providing actionable information rather than just a better means of collecting data.

  • Midstream:

Since companies in this sector make the most profits through maintaining a consistent flow of products at a target capacity, data analytics will play a major role in maintaining the same. Opportunities can be created to improve the flow of money in the form of oil/gas by tapping into the real-time data streams from remote destinations. Machine learning and augmented intelligence can be an added advantage. 

The Appeal of Big Data in Oil and Gas:

In Conclusion, we can say that data is equivalent to oil where economic growth is taken into account. On spotting the future prospects and opportunities, enterprises have started spending a hefty amount of money on finding out behavioral patterns in the data that is taken into the account which is in turn processed and used to optimize the production and thus help the company stir towards the economic upturn.

– By Darshil Shah and Kartik Mawa

Maharashtra Institute of Technology, Pune, India. 

Note: – Every year Crude Companion organizes article writing competition under MIT-SPE AIIIP. Since last two years it has been a great experience working with highly motivated student members of MIT. We really appreciate their enthusiasm and dedication. This is the winning article of AIIIP 2018 competition.

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12 thoughts on “Article: More Barrels Per Data”

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